This paper reviews approaches for automated pattern spotting and knowledge discovery in
spatially referenced data. This is an emerging field which to date has received …

Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are
homogeneous and/or well separated. As many types of clustering and criteria for …

The capacitated clustering problem (CCP) is the problem in which a given set of weighted
objects is to be partitioned into clusters so that the total weight of objects in each cluster is …

Provides explanatory text, illustrative mathematics and algorithms, demonstrations of the
iterative process, pseudocode, and well-developed examples for (familiar as well as novel) …

The Capacitated p-median problem (CPMP) seeks to solve the optimal location of p
facilities, considering distances and capacities for the service to be given by each median. In …

Cluster analysis continues to be an important exploratory technique in scientific inquiry. It is
used widely in geography, public health, criminology, ecology, and many other fields …

Constrained Clustering allows to make the clustering task more accurate by integrating user
constraints, which can be instance-level or cluster-level constraints. Few works consider the …

Finding modules, or clusters, in networks currently attracts much attention in several
domains. The most studied criterion for doing so, due to Newman and Girvan [Phys. Rev. E …

Genetic algorithms (GAs) have recently been accepted as powerful approaches to solving
optimization problems. It is also well-accepted that building block construction (schemata …

Conflicting opinions from environmental advocates and economic interests on the best
strategy for management of public lands often leaves land managers in a difficult position …